
\section{What This All Means}

YOLOv3 is a good detector. It's fast, it's accurate. It's not as great on the COCO average AP between .5 and .95 IOU metric. But it's very good on the old detection metric of .5 IOU.

Why did we switch metrics anyway? The original COCO paper just has this cryptic sentence: ``A full discussion of evaluation metrics will be added once the evaluation server is complete''. Russakovsky et al report that  that humans have a hard time distinguishing an IOU of .3 from .5! ``Training humans to visually inspect a bounding box with IOU of 0.3 and distinguish it from one with IOU 0.5 is surprisingly difficult.'' \cite{russakovsky2015best} If humans have a hard time telling the difference, how much does it matter?

But maybe a better question is: ``What are we going to do with these detectors now that we have them?'' A lot of the people doing this research are at Google and Facebook. I guess at least we know the technology is in good hands and definitely won't be used to harvest your personal information and sell it to.... wait, you're saying that's exactly what it will be used for?? Oh.

Well the other people heavily funding vision research are the military and they've never done anything horrible like killing lots of people with new technology oh wait.....\footnote{The author is funded by the Office of Naval Research and Google.}

I have a lot of hope that most of the people using computer vision are just doing happy, good stuff with it, like counting the number of zebras in a national park \cite{parham2017animal}, or tracking their cat as it wanders around their house \cite{scott_2017}. But computer vision is already being put to questionable use and as researchers we have a responsibility to at least consider the harm our work might be doing and think of ways to mitigate it. We owe the world that much.

In closing, do not @ me. (Because I finally quit Twitter).
